<html><head><title>Data Scientist - Brooklyn, NY</title></head>
<body><h2>Data Scientist - Brooklyn, NY</h2>
<h2 class="jobSectionHeader"><b>Job Description:
</b></h2><h3 class="jobSectionHeader"><p><b>Key Responsibilities:
</b></p><p><b>As a Data Scientist you’ll be a core member of our Fast Forward Labs Application Development team. This is a client facing position. You will spend most of your time building machine learning models to tackle real life business problems through asking the right questions, understanding proprietary and publicly available data, extracting and leveraging insights from the data, and communicating both process and outcome to business stakeholders.
</b></p><p></p><p><b>Skills and Qualifications:
</b></p><p></p><p><b>This position requires a strong math background, with a particular focus on machine learning algorithms and comfort with quantitative analysis.
</b></p><p></p><p><b>You should be quite familiar with leading practices in the machine learning lifecycle, including data preparation for analysis, ML model selection, training and validation. We also expect that you have experience with preparing ML models for production.
</b></p><p></p><p><b>We expect you to be a strong programmer, and willing to embrace software engineering best practices. We primarily work in Python for research code but are always open to the best technologies for a given problem.
</b></p><p></p><p><b>You should also have a background in current CI/CD and DevOps practices. Working knowledge of the Kubernetes ecosystem and production-grade ML systems is a plus.
</b></p><p></p><p><b>You should be comfortable to diving into diverse forms of data in order to help define questions that can and should be answered
</b></p><p></p><p><b>We often find in applied machine learning that the art of asking the right question is more of a challenge than finding the answer. We expect you’ll be enthusiastic and skilled at formulating the right questions and thinking strategically. Sometimes the simplest solution is the best answer.
</b></p><p></p><p><b>You should have spent at least 3 years as a practicing data scientist or machine learning engineer.
</b></p><p></p><p><b>In your past, you should have completed a degree program in a computationally intensive quantitative field (e.g. CS, physics, neuroscience, operations management, operations research) </b><b>or </b><b>demonstrated relevant experience in using data science and machine learning to solve business problems.
</b></p><p></p><p><b>We expect that you have extensive experience using python (+ pandas) for statistical analysis and machine learning.
</b></p><p></p><p><b>We would also love to learn about your experiences working with supervised (e.g. regression, classification) and unsupervised machine learning techniques.
</b></p><p></p><p><b>At Fast Forward Labs, we believe that you should do what you love most of the time. As such, you should have a keen interest in ability to creatively combine algorithms to solve novel problems. In addition it should excite you to explain nuanced technical work to business stakeholders in plain language, and to create effective data visualizations. Of course, it’s important that you enjoy working with business stakeholders, data engineers, product engineers, model deployment teams.
</b></p><p></p><p><b>Because this is a development-focused role, you should have familiarity with production ready code, testing frameworks, and collaborative coding environments (e.g. git).
</b></p><p></p><p><b>Who We Are
</b></p><p><b>Cloudera Fast Forward Labs is an applied machine learning research group within Cloudera that helps organizations recognize and develop new product and business opportunities through emerging machine learning and AI technologies. We offer a research subscription service, consulting services and advisory services to companies in a wide set of industries.
</b></p><p></p><p><b>We support our clients by helping them create powerful data products, help businesses capture the value of emerging data capabilities, and bring the lessons learned through that work to our research process.
</b></p><p></p><p><b>We value thoughtfulness, curiosity, creativity, and diverse perspectives. This position is based in our Brooklyn office.</b></p></h3></body>
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